As mental health (MH) disorders become increasingly prevalent, their multifaceted
symptoms and comorbidities with other conditions introduce complexity to diagnosis, posing …

In recent years, tremendous progress has been made in surgical practice for example with
Minimally Invasive Surgery (MIS). To overcome challenges coming from deported eye-to …

Deep neural networks excel at finding hierarchical representations that solve complex tasks
over large datasets. How can we humans understand these learned representations? In this …

Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …

Accurate and robust visual object tracking is one of the most challenging and fundamental
computer vision problems. It entails estimating the trajectory of the target in an image …

Abstract The Visual Object Tracking challenge VOT2018 is the sixth annual tracker
benchmarking activity organized by the VOT initiative. Results of over eighty trackers are …

We propose a general framework called Network Dissection for quantifying the
interpretability of latent representations of CNNs by evaluating the alignment between …

Abstract In recent years, Discriminative Correlation Filter (DCF) based methods have
significantly advanced the state-of-the-art in tracking. However, in the pursuit of ever …

In the field of generic object tracking numerous attempts have been made to exploit deep
features. Despite all expectations, deep trackers are yet to reach an outstanding level of …

Today, a new generation of artificial intelligence has brought several new research domains
such as computer vision (CV). Thus, target tracking, the base of CV, has been a hotspot …